Abstract P195: Long-Term Outcomes Associated with Hospital-Acquired Thrombocytopenia Among Patients with Acute Coronary Syndrome
Bibliographic record
Abstract
Background Prior studies demonstrated that the development of thrombocytopenia (platelet count drop to <100x10 9 /L) during an ACS hospitalization is associated with adverse outcomes. The long-term prognosis associated with thrombocytopenia of milder severity (100-149x10 9 /L) is less clear. Methods We examined 7,435 ACS patients enrolled in the SYNERGY trial (a randomized comparison between unfractionated and low molecular weight heparin) who had normal platelet counts (≥150x10 9 /L) at admission. Mild thrombocytopenia was defined as a platelet count drop to a nadir of 100-149x10 9 /L; moderate-severe thrombocytopenia was defined as <100x10 9 /L. Patients with nadir platelet counts occurring after in-hospital CABG were excluded. Cox models were used to compare risks of 30-day GUSTO moderate-severe bleeding and 1 year mortality between groups after adjusting for baseline clinical factors. Results Overall, 720 patients (9.7%) developed mild thrombocytopenia and 83 (1.1%) developed moderate-severe thrombocytopenia. Nadir platelet counts occurred at a median of 1.4 days (interquartile range 0.7 - 2.5) after admission. Patients who developed thrombocytopenia were older (median age 71 vs. 67 years, p<0.001) and more often male (71% vs. 63%, p<0.001). Compared with non-thrombocytopenic patients, patients with mild thrombocytopenia were as likely to be prescribed aspirin (90.6% vs. 90.1%) and clopidogrel (65.2% vs. 64.9%) at discharge, whereas patients with moderate-severe thrombocytopenia were less likely to receive aspirin (66.2%) and clopidogrel (44.6%) therapy (both p<0.001). Thrombocytopenia was associated with increased 30-day GUSTO moderate-severe bleeding and 1-year mortality risks (Table) compared with no thrombocytopenia. Conclusions Thrombocytopenia occurs in more than 1 of 10 ACS patients. Our findings suggest that even mild thrombocytopenia is clinically relevant and associated with increased downstream bleeding and mortality risks. Risks of Adverse Events Unadjusted Rate Adjusted Hazard Ratio (95% confidence interval) 30-day GUSTO mod-severe bleeding No thrombocytopenia 5.9% Reference Mild thrombocytopenia 10.0% 1.83 (1.34 - 2.51) Mod-severe thrombocytopenia 34.3% 6.88 (4.08 - 11.59) 1-year Mortality No thrombocytopenia 6.5% Reference Mild thrombocytopenia 9.8% 1.30 (1.00 - 1.69) Mod-severe thrombocytopenia 27.7% 5.02 (3.22 - 7.84)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".